Power System Spare Capacity Measurement Method Based on Multi-Constraint Security Domain Projection

Abstract

The present invention provides a method for calculating the reserve capacity of a power system based on multi-constraint security domain projection, which relates to the technical field of power grid operation control. By using the interval power flow method to extract the characteristic quantities of power grid power flow fluctuations to construct a state space representing the operating state of the power grid and linearly transforming it to a two-dimensional projection plane, the operating domain is obtained and the section limit constraint is introduced to obtain the single-section limit constraint security domain. The boundaries of the multi-section constraint security domains for two different operating scenarios are characterized respectively according to the principles of maximizing the sum of the global areas and maximizing the operating margin of the given power nodes. A random fluctuation model of the operating state of the power nodes is established, and an effective reserve formula is given according to the shortest distance and direction between its fluctuation boundary and the boundaries of the multi-section limit constraint security domains corresponding to each section under any operating scenario, so as to calculate the reserve capacity of the power system, which can adapt to the massive working condition combinations caused by the random fluctuations of high-proportion new energy output and ensure the safe and orderly operation of the power grid under random fluctuations.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid operation control, and particularly relates to a method for calculating reserve capacity of a power system based on projection of a multi-constraint security region. Background Art

[0002] In the context of high proportion of new energy access to the power grid, the output of new energy generation represented by wind power and photovoltaic power is directly coupled with meteorological parameters. Due to the strong uncertainty of the weather change process, and the low accuracy and spatio-temporal refinement degree of meteorological information forecasting in the existing technology, the output of a large amount of new energy shows great randomness, volatility and intermittency, which are concentrated in that the net injection power distributed at each node of the power grid fluctuates randomly to varying degrees with the prediction error of new energy output.

[0003] When the power flow of both new energy and load nodes in the power grid shows random fluctuations simultaneously, the number of their combination modes is astonishing, resulting in the inability to check one by one the line blockages caused by the combined working conditions of node power flow fluctuations. The incomplete pre-check of line blockages often leads to insufficient reserve capacity of the whole network or uncontrollable section limits, bringing serious accident losses to the power grid. Therefore, the application of traditional power grid dispatching theory and technology in the new power system has shown lag and failure, and only checking typical working conditions with only statistical significance, or reviewing and learning the control strategies for historical working conditions, far from being able to adapt to the massive working condition combinations caused by the random fluctuations of new energy output at present, and the power dispatching operation control has gradually entered the "no man's land".

[0004] In short, in a power system with high proportion of new energy access, the strong randomness, volatility and intermittency of new energy output lead to a sharp increase in the number of combined working conditions of power grid node power flow. The existing methods are difficult to adapt to the massive working conditions, easily cause line blockages and insufficient reserve capacity, threatening the safe operation of the power grid.

[0005] Based on this, the present invention is proposed. Summary of the Invention

[0006] The object of the present invention is to provide a method for calculating reserve capacity of a power system based on projection of a multi-constraint security region, which can adapt to the massive working condition combinations caused by the random fluctuations of high proportion of new energy output, avoid accidents of insufficient reserve capacity of the whole network or uncontrollable section limits caused by line blockages, and ensure the safe and orderly operation of the power grid under random fluctuations.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A method for calculating reserve capacity of a power system based on projection of a multi-constraint security region, comprising:

[0009] S1: Extract the power flow fluctuation characteristic quantities of the power grid by the interval power flow method to construct a state space representing the operating state of the power grid, linearly transform the state space to a two-dimensional projection plane reflecting the relationship between section power and system power, and then obtain the operating domain satisfying the constraint conditions by determining the upper and lower boundary functions;

[0010] S2: Introduce the section limit constraint on the basis of the operating domain to obtain the single-section limit constraint safety domain;

[0011] S3: Combine the acquisition method of the single-section limit constraint safety domain and, based on the principle of maximizing the sum of the global areas and maximizing the operating margin of the given power nodes, depict the boundaries of two multi-section limit constraint safety domains respectively for application to the operating scenarios with unknown and known current operating states of the power nodes;

[0012] S4: Establish a stochastic fluctuation model for the operating state of the power nodes, give an effective reserve formula according to the shortest distance and direction between the fluctuation boundary of the model and the boundaries of the multi-section limit constraint safety domains corresponding to each section in any of the said operating scenarios, and measure the reserve capacity of the power system through the effective reserve formula.

[0013] The present invention provides a preferred solution. S1 includes: S11: Introduce interval variables to model the fluctuation ranges of new energy and load and the adjustable range of the units, form a power flow equation containing interval variables, and define the nodes with new energy and / or load as power nodes; S12: Obtain the initial state points of the unit nodes and power nodes in space at any moment as the state space, and calculate the branch power flows between the nodes; S13: Construct a two-dimensional projection plane 1 with section power as the y-axis and system power as the x-axis according to the branch power flows, system total power, and power flow equation, set the section limit constraint and balance power constraint, and split and map the initial state points on the two-dimensional projection plane 1 to obtain the unit and power state points of the first projection; S14: Combine the transformation of the system power with the deformation of the power balance constraint, split and map the initial state points on the two-dimensional projection plane 2 with section power as the y-axis and the transformed system power as the x-axis to obtain the unit and power state points of the second projection; S15: Define the upper and lower boundary functions of the unit and power state points of the second projection respectively, and obtain two piecewise linear and closed polygon envelopes, and the enclosed areas are the operating domains of the units and power nodes respectively.

[0014] More preferably, in S11, the modeling adopts the affine-linear optimization method, incorporates the adjustable range of the units and the fluctuation ranges of new energy and load nodes into the node injection power respectively, and establishes an affine-linear equation representing the fluctuation.

[0015] The present invention provides a preferred solution. S2 includes: transforming the section power in combination with the deformation of the section limit constraint, performing a transformation on the unit node operating region obtained in S15 by first symmetrically flipping it about the x-axis and then translating it upward by a distance equal to the section limit size to obtain the transformed unit operating state, and completing the multiple splitting and mapping of the initial state point on the two-dimensional projection plane three with the transformed section power as the y-axis and the transformed system power as the x-axis to obtain the unit and power state points of the three projections with single-section constraint. Define the intersection of the region below the upper boundary function of the transformed unit operating state and the entire region of the power node operating region as the single-section limit constraint safety region.

[0016] The present invention provides a preferred solution. In S2, a unit scheduling scheme that maximizes the area of the single-section limit constraint safety region is given.

[0017] More preferably, in S2, the unit scheduling scheme that maximizes the area of the single-section limit constraint safety region adopts: the units increase their output in sequence on the upper boundary of the single-section limit constraint safety region.

[0018] The present invention provides a preferred solution. In S3, the method for maximizing the sum of the areas of the entire regions is the method for obtaining the boundary of the safety region with the largest area after bringing all sections into the same coordinate system.

[0019] The present invention provides a preferred solution. In S3, the method for maximizing the given power node operating margin includes: for the initial power state point in the initial state point, setting the section limit and constraint conditions. When there is a solution for the vector in the constraint conditions, setting the objective function and solving the objective function to obtain the optimal solution of the vector; then classifying all units into two segments according to the optimal solution of the vector, the first category being all the segments with increased output, and the second category being all the segments without increased output, and then forming the sorting methods for the units in the first category and the second category respectively according to the single-section limit constraint safety region obtaining method, thus forming the boundary of the multi-section limit constraint safety region.

[0020] The present invention provides a preferred solution. S4 includes: S41: Assume that each power node changes with a power state point as the center at a volatility, and the change range is , all power node fluctuations are reflected in the operation domain. With the power state point as the center, the polygon envelope formed by the operation domain of power nodes with the side length reduced to 2λ of the original length is the fluctuation interval polygon envelope. When the volatility λ gradually increases, the fluctuation interval polygon envelope increases proportionally with the power state point as the center; S42: Assume that the center of the power state point function is located inside the safety domain corresponding to the observed cross-section. Connect the center of the power state point function with each vertex of the polygon envelope of the power node fluctuation interval and extend it. The extended line intersects with the boundary of the safety domain to obtain the intersection point of the extended line and the safety domain boundary. When the ratio of the length d1 of the connection line from the intersection point to the center of the power state point function to the length d0 of the connection line from the corresponding vertex to the center of the power state point function is the smallest, this d1 is the shortest fluctuation distance from the power node function center to the unit node function; S43: Define the product of the shortest fluctuation distance and the reserve coefficient as the effective reserve of this cross-section . When considering all cross-sections of the system, take the minimum value of the effective reserve among them and define it as the system effective reserve R:

[0021] .

[0022] Compared with the prior art, the technical solution of the present invention has the following advantages:

[0023] The present invention deconstructs the operation scenario where the power flow of the power supply nodes connected to the load and new energy grid connection has a time-varying bounded fluctuation interval, linearly models the volatility of the load and new energy output, then uses the interval power flow method to examine the influence of the power flow change of each node under the fluctuation model on the branch power flow, and further constructs the projection model of the safety domain in the two-dimensional state space of section power - balance power. On this basis, a method for determining the unit reserve measurement considering the fluctuations of the load and new energy is developed. It is a scientific and complete method for efficiently measuring the reserve capacity of a high-proportion new energy power system based on the projection of a multi-constraint safety domain, which can adapt to the massive working condition combinations caused by the random fluctuations of high-proportion new energy output, avoid accidents such as insufficient network-wide reserve capacity caused by line congestion or uncontrollable section limits, and ensure the safe and orderly operation of the power grid under random fluctuations. Description of the Drawings

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the provided drawings.

[0025] Figure 1 It is the flowchart of the method for measuring the reserve capacity of a power system based on the projection of a multi-constraint safety domain provided by a specific embodiment of the present invention;

[0026] Figure 2 Schematic diagram of the operating region obtained by the method for calculating the reserve capacity of the power system based on the projection of the multi-constraint security region provided by a specific embodiment of the present invention;

[0027] Figure 3 Schematic diagram of the security region (single-section limit constraint) obtained by the method for calculating the reserve capacity of the power system based on the projection of the multi-constraint security region provided by a specific embodiment of the present invention;

[0028] Figure 4 Position relationship diagram of the operating region in the scenario where the method of maximizing the sum of the global areas is not applicable in the method for calculating the reserve capacity of the power system based on the projection of the multi-constraint security region provided by a specific embodiment of the present invention;

[0029] Figure 5 Schematic diagram of the process of delimiting the security region after obtaining the optimal solution of the unit by the method of maximizing the margin of a given power node in the method for calculating the reserve capacity of the power system based on the projection of the multi-constraint security region provided by a specific embodiment of the present invention;

[0030] Figure 6 Schematic diagram of the position relationship between the fluctuation of the power state points characterized by the polygon envelope of the fluctuation interval and the security region in the method for calculating the reserve capacity of the power system based on the projection of the multi-constraint security region provided by a specific embodiment of the present invention.

[0031] Figure 7 Schematic diagram of the process of obtaining the effective reserve by the analytical geometry method in the method for calculating the reserve capacity of the power system based on the projection of the multi-constraint security region provided by a specific embodiment of the present invention. Specific Embodiment

[0032] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0033] Please refer to Figure 1 , this embodiment provides a method for calculating the reserve capacity of the power system based on the projection of the multi-constraint security region, which is mainly implemented through the following steps:

[0034] S1: Use the interval power flow method to extract the power flow fluctuation characteristic quantities of the power grid to construct the state space representing the operating state of the power grid, linearly transform the state space to the two-dimensional projection plane reflecting the relationship between the section power and the system power, and then obtain the operating region satisfying the constraint conditions by determining the upper and lower boundary functions;

[0035] S2: Introduce cross-section limit constraints on the basis of the operation domain to obtain the single-cross-section limit constraint security domain;

[0036] S3: Combine the acquisition method of the single-cross-section limit constraint security domain and, based on the principles of maximizing the sum of the global areas and maximizing the operation margin of the given power nodes, depict the boundaries of two multi-cross-section limit constraint security domains respectively, for application to the operation scenarios of unknown current power node operation states and known current power node operation states;

[0037] S4: Establish a random fluctuation model for the operation state of power nodes, and give an effective reserve formula according to the shortest distance and direction between the fluctuation boundary of the model and the boundaries of the multi-cross-section limit constraint security domains corresponding to each cross-section in any of the above operation scenarios, and measure the reserve capacity of the power system through the effective reserve formula.

[0038] This embodiment deconstructs the operation scenarios with time-varying bounded fluctuation intervals of the power flow of the load and new energy grid-connected power supply nodes, linearly models the volatility of the load and new energy output, and then uses the interval power flow method to examine the impact of the power flow changes of each node under the representation of the fluctuation model on the branch power flow, and further constructs a projection model of the security domain in the two-dimensional state space of cross-section power - balanced power. On this basis, a method for calculating the unit reserve considering the fluctuations of the load and new energy is developed, which can efficiently calculate the reserve capacity, adapt to the massive working condition combinations caused by the random fluctuations of the high proportion of new energy output, avoid accidents such as insufficient grid-wide reserve capacity caused by line congestion or uncontrollable cross-section limits, and ensure the safe and orderly operation of the power grid under random fluctuations.

[0039] In a preferred implementation manner, on the basis of the above implementation manner, step S1: Use the interval power flow method to extract the power flow fluctuation characteristic quantities of the power grid to construct a state space representing the operation state of the power grid, linearly transform the state space to a two-dimensional projection plane reflecting the relationship between cross-section power and system power, and then obtain the operation domain satisfying the constraint conditions by determining the upper and lower boundary functions, which is specifically implemented as follows:

[0040] S11: Introduce interval variables to model the fluctuation ranges of new energy and load and the adjustable range of the unit, form a power flow equation containing interval variables, and define the nodes with new energy and / or load as power nodes.

[0041] This embodiment introduces interval variables to model the adjustable range of the power system unit and the fluctuation ranges of new energy and load nodes, and forms a power flow equation containing interval variables (the following and ), and its solution set is presented in the form of upper and lower bound envelopes, which includes all possible deterministic power flow solutions and directly reflects all possible operating states of the power grid. For the modeling form of interval variables, that is, the power flow equation containing interval variables, in a preferred implementation manner, the modeling method adopts the affine-linear optimization method, taking the adjustable range of the unit and the fluctuation ranges of new energy and load nodes into account in the nodal injection power respectively, and establishing an affine-linear equation, the expression of which is as follows:

[0042] ;

[0043] Among them, represents the affine variable of the fluctuation of the unit at node i (the unit mentioned throughout the text specifically refers to the thermal power unit), new energy or load, is the fluctuation amplitude of the power at node i, is the fluctuation noise element of the power at node i, has a value range of [0, 1]. When represents the affine variable of the unit fluctuation, is the base value of the unit output, takes the lower bound when it is a positive value. Since from the perspective of dispatching, the fluctuations of load and new energy output both originate from prediction errors, in this embodiment, the load and new energy output at the same node in the power system are considered together and represented by the same affine-linear fluctuation quantity, and a node with at least one of load and new energy is defined as a power node. When represents the affine variable of the power node fluctuation, is the difference between the new energy output and the load base value at the node, and usually takes the absolute value upper bound when it is a negative value. Considering the characteristics of the fluctuation quantity of new energy units, since the installed capacity of new energy corresponding to each main transformer is fixed, the fluctuation amplitude caused by the change of new energy output is basically determinable. When a power node only contains new energy units, the maximum fluctuation amplitude can be characterized by a constant available at each moment. Considering the characteristics of the load fluctuation quantity, this embodiment mainly examines the influence of temperature change on the load fluctuation amplitude. Since the temperature change is relatively smooth and the temperature-sensitive load has a large hysteresis, it is applicable to determine the fluctuation interval on a monthly time scale.

[0044] In addition, it should be noted that the affine-linear equation is a representation method of the power of units, loads and new energy nodes with two variables, and the power flow equation is an equation for calculating the section power flow according to the power variables of each node and the grid structure data.

[0045] S12: Obtain the initial state points of the unit nodes and power nodes at any moment in space as the state space, and calculate the branch power flow between each node.

[0046] Let the number of grid units and the number of power nodes be \(n\) and \(m\) respectively. According to the affine linear equation established in step S11, the operating state of the power grid at time \(t\) can be represented as a state point in the \((n + m)\)-dimensional space as follows:

[0047] ;

[0048] When the reference curves of each node are determined, the state point of the operating state of the power grid at time \(t\) is a point that fluctuates around the reference curve with fluctuations.

[0049] According to the DC power flow calculation method, let the inverse matrix of the admittance matrix \(Y\) of the power grid nodes (here, the nodes refer to the nodes on the grid structure, and these nodes are power nodes and / or unit nodes) be \(B\). The element in the \(k\)-th row and \(j\)-th column of the \(B\) matrix is represented by characterize, represents the element in the \(k\)-th row and \(j\)-th column of the \(B\) matrix, is the branch admittance coefficient between nodes \(k\) and \(j\) and = - . To make the \(Y\) matrix non-singular, let be the reference node and = 0, then the branch power flow can be expressed as:

[0050] ;

[0051] where, is the branch admittance coefficient between nodes \(j\) and \(k\), represents the element in the \(k\)-th row and \(i\)-th column of the \(B\) matrix, represents the element in the \(j\)-th row and \(i\)-th column of the \(B\) matrix.

[0052] The total system power can be expressed as:

[0053] ;

[0054] S13: Construct a two-dimensional projection plane with the sectional power as the \(y\)-axis and the system power as the \(x\)-axis - , and set the sectional limit constraint and the balance power constraint. Split and map the initial state point on the two-dimensional projection plane - to obtain the unit and power state points of the first projection.

[0055] Substitute the affine linear equation characterizing the fluctuations into the above two equations ( and ), and denote the sensitivity coefficient of the power of node \(i\) to the branch power flow of branch \(kj\) , is the branch admittance coefficient of the branch cross-section taken for the two-dimensional projection (the y-axis of the two-dimensional projection plane refers to the cross-section current of the specific cross-section being observed, so each plane corresponds to only one branch). Construct a two-dimensional projection plane of the operating state space with the cross-section power as the y-axis and the system power as the x-axis, and the expression is as follows: The expression is as follows:

[0056] ;

[0057] ;

[0058] According to the cross-section limit constraint and the power balance constraint, denote the cross-section limit of the branch cross-section taken for the two-dimensional projection as , and we have:

[0059] ;

[0060] ;

[0061] To obtain the detailed information about the unit nodes and power nodes, in a preferred embodiment, the n unit nodes and m power nodes are examined separately. According to the affine linear equation established in step S11, define the initial unit state point as , the initial power state point as , and correspondingly split the cross-section power and the system power into the unit cross-section power , the unit system power , the power cross-section power and the power system power . Among them, represents the base value of the output of unit node i, represents the fluctuation amplitude of unit node i, represents the fluctuation noise element of unit node i, represents the difference between the new energy output and the load base value at power node i, represents the fluctuation amplitude of power node i, represents the fluctuation noise element of power node i. Then the two constraint equations can be split as follows:

[0062] ;

[0063] ;

[0064] Denote respectively represent the influence parts of unit regulation on the balanced power and section power, respectively represent the influence parts of power node fluctuations on the balanced power and section power, where, represents the sensitivity coefficient of the power of unit node i to the power flow of the observed branch, represents the sensitivity coefficient of the power of power node i to the power flow of the observed branch. The two-dimensional projection unit state point is defined using the balanced power and section power and the power state point , which represents the initial unit state point , the power state point is the projection point on the two-dimensional plane with the section power as the y-axis and the system power as the x-axis, that is, the unit and power state points of the first projection are obtained. Plane - The original constraint equation is simplified to:

[0065] ;

[0066] ;

[0067] where , , , The expressions are:

[0068] ;

[0069] ;

[0070] ;

[0071] ;

[0072] S14: Combine the transformation of the power balance constraint to transform the system power to obtain , and split and map the initial state point on the two-dimensional projection plane - to obtain the unit and power state points of the second projection.

[0073] Transform the power balance constraint expression to obtain the following expression:

[0074] ;

[0075] Denote , , this transformation aims to clear the base value of the unit output to directly reflect the adjustable amount of the unit at each moment, which is convenient for the dispatcher to observe and record the unit dispatching plan. After the above transformation, the two-dimensional projection unit state point and power state points Remapped as unit state points and power state points That is, the unit and power state points of the secondary projection are obtained.

[0076] S15: Define the upper and lower boundary functions of the unit and power state points of the secondary projection respectively, and obtain two piecewise linear and closed polygon envelopes. The enclosed areas are the operation domains of the unit and power nodes respectively.

[0077] For a general piecewise linear function , , is a constant.

[0078] ;

[0079] Denote The piecewise linear function at time is The piecewise linear function at time . It is easy to prove that for any x and any permutation, there is , that is , constitutes the upper and lower envelopes of all paths of x from 0 to .

[0080] According to the above piecewise linear function theorem, denote = and define the upper boundary function of all operating conditions of the unit state point in the two-dimensional plane as:

[0081] ;

[0082] ;

[0083] Correspondingly, the lower boundary function is:

[0084] ;

[0085] ;

[0086] Similarly, according to the above piecewise linear function theorem, denote = , = , then , then define the upper boundary function of all operating conditions of the power state point in the two-dimensional plane as:

[0087] ;

[0088] ;

[0089] Correspondingly, the lower boundary function is:

[0090] ;

[0091] ;

[0092] Due to the same starting and ending points, the piecewise linear envelopes of the operating states of the unit and the power node determined by the above formula can enclose closed polygons in the - two-dimensional plane respectively. The regions enclosed by the two polygon envelopes will include all operating states of the unit and the power node within the fluctuation range. Therefore, the regions enclosed by the polygons are called the unit node operating domain and the power node operating domain respectively. Since the left and right sides of the power balance constraint are the abscissas of the unit and the power node respectively, therefore, from the power balance constraint after deformation in the above text , for two points representing the operating states of the unit and the power node at the same moment, they are always on the same vertical line. Then the system operating domain should satisfy: when = = , and hold simultaneously, that is, the equal parts in the two operating domains . At the same moment, the operating state point is not only within the operating domain envelope, but also needs to satisfy the same abscissa. When the number of units and power nodes considered is large enough, this polygon can be approximately regarded as an ellipse, as shown in Figure 2 . Figure 2 In [figure reference], the yellow arc represents the upper boundary function of the unit node operation, the black arc represents the lower boundary function of the unit node operation, the red arc represents the upper boundary function of the power node operation, and the blue arc represents the lower boundary function of the power node operation. The enclosed part is the unit node operating domain, The enclosed part is the power node operating domain.

[0093] In a more preferred embodiment, S2: On the basis of the operating domain, introduce the section limit constraint to obtain the single-section limit constraint safety domain, and give the unit scheduling scheme that maximizes the area of the single-section limit constraint safety domain, which is mainly achieved through the following steps: Combine the deformation of the section limit constraint to transform the section power to obtain , the operation domain of the unit nodes obtained in S15 is first symmetrically flipped about the x-axis and then translated upward by a distance equal to the section limit size to obtain the transformed operation state of the unit, completing the transformation of the initial state point in the section power after transformation as the y-axis, and the transformed system power as the x-axis in the two-dimensional projection plane three - is split and mapped multiple times to obtain the unit and power state points of the three projections with single-section constraints. The intersection of the following area of the upper boundary function of the transformed unit operation state and the entire domain of the power node operation domain is defined as the single-section limit constraint safety domain. The more detailed steps are as follows:

[0094] The section limit constraint inequality is deformed and sorted out to get:

[0095] ;

[0096] Denote , , that is, there is:

[0097] ≥ ;

[0098] It can be seen from the transformation relationship that the above transformation will only affect the operation domain of the unit obtained in S15 (that is, the operation domain of the unit formed by the envelope of the upper and lower boundary functions of the projection points of the initial unit state point on the two-dimensional plane - ). The original operation domain of the unit is first symmetrically flipped about the horizontal axis (x-axis) and then translated upward by a distance , that is, from Figures 2 to 3 transforms. So far, after multiple rounds of mapping, the initial unit state point , the initial power state point are mapped to the unit state point and the power state point , that is, the unit and power state points of the three projections are obtained, and their coordinates satisfy the following characteristics:

[0099] ≥ ;

[0100] ;

[0101] In the formula, is the transformed unit section power, is the transformed unit system power, is the transformed power section power, is the transformed power system power. The geometric meaning of the above expression is that for any power state point , x = corresponding must exist and be located above the power state point . The set of all operating state points where the operating state of the power node is located within the polygon area enclosed by the upper and lower envelopes of the transformed operating domain and satisfies the above position relationship constitutes the "safe domain". That is, as Figure 3 shown, the range of the "safe domain" on the two-dimensional plane can be described as: the intersection of the area below the upper boundary function of the transformed unit operating state and the entire polygon of the power node operating state. The "safe domain" obtained in this step is the single-section limit constraint safe domain, and its essence is the characterization of the safe fluctuation range of the power node. Figure 3 In, the part enclosed by the yellow arc and the black arc is the operating domain of the unit node before transformation, that is, the Figure 2 obtained in step S15 and enclosed part; the part enclosed by the red arc and the dark blue arc is the operating domain of the power node, that is, the Figure 2 obtained in step S15 and enclosed part is the operating domain of the power node; the part enclosed by the green arc and the light blue arc is the operating domain of the unit node after transformation through step S2; the shaded part is the "safe domain" obtained through step S2, that is, the function and enclosed part.

[0102] In a more preferred embodiment, S2: Based on the operating domain, sectional limit constraints are introduced to obtain a single-sectional limit constraint security domain, and then a unit scheduling scheme that maximizes the area of the single-sectional limit constraint security domain is given. The single-sectional limit security domain is formed by the intersection of the envelope of the unit operating domain and the envelope of the power node operating domain according to certain rules. Based on this embodiment, a sorting method for increasing the unit output is given. This sorting method is the way of increasing the output that constitutes the boundary of the unit operating domain. The unit scheduling scheme that maximizes the area of the single-sectional limit constraint security domain adopts: the units increase their output in sequence along the upper boundary of the single-sectional limit constraint security domain. Specifically as follows: The upper boundary function of the transformed unit operating state can be considered as the maximum value of the sectional power flow that can be borne by the observed section when the unit exerts the maximum ability to reduce the sectional power flow, which is caused by the fluctuations of the power nodes. The part within the power node operating domain that is less than this maximum value is the safe range of fluctuations for the power nodes. For all unit scheduling schemes, it is easy to know that when the area of the security domain is the largest, the safety margin of power node fluctuations is the most sufficient. To make the security domain the largest, the scheduling scheme for a single section should make the unit exert the maximum ability to reduce the sectional power flow, that is, take the upper boundary of the unit operating domain after multiple projections. The unit scheduling scheme corresponding to this boundary can be described as: when the net load obtained by subtracting the new energy output from the power node load changes from low to high, the unit output starts from the lowest, and in sequence, the output is increased in ascending order according to the sensitivity coefficient from negative to positive and from small to large. In this way, the upper boundary of the unit operating domain after the second projection can be obtained, and at this time, the area of the unit operating domain is the largest, and it has the largest safety margin for different power node fluctuations. According to the above elaboration of the mathematical theorem of the envelope line of piecewise linear functions, for a cluster of piecewise linear functions, only by arranging the function segments in ascending order according to the coefficients from small to large can the upper envelope (upper boundary function) be formed, and the upper envelope corresponds to the above unit scheduling scheme.

[0103] The strategy of the units increasing their output in sequence along the upper boundary of the single-sectional limit constraint security domain ensures the continuity of unit regulation. As long as the units are adjusted along the upper boundary, it can be ensured that the net load distribution of all power nodes within the security domain will not exceed the limit. However, if the net load distribution of the power nodes is located outside the security domain, no matter how the units are adjusted, they will surely exceed the limit. Therefore, the distance between the power state points within the security domain and the boundary can reflect the operating margin. For the security domain under single-section constraints, the boundary determined by the above method is globally optimal.

[0104] S3: Combine the acquisition method of the single-section limit constraint security region, and with the principle of maximizing the sum of the global areas and maximizing the operating margin of the given power nodes, depict the boundaries of the two multi-section limit constraint security regions respectively, so as to be applied to the security region boundary depiction in the operating scenarios of unknown and known current operating states of power nodes. Considering the method for obtaining the security region boundary under multi-section constraints, the difficulty lies in that at this time, the unit regulation must simultaneously consider the collaborative impact on all section limits, that is, the maximum delimitation method of the security region is equivalent to the optimal regulation strategy of the unit under the condition of the maximum security margin of all considered sections. The present invention provides two methods for delimiting the unit security region under multi-section constraints.

[0105] First is the maximum area delimitation method, that is, maximizing the sum of the global areas, that is, the method for obtaining the security region boundary with the largest area after incorporating all sections into the same coordinate system. Therefore, the global region corresponds to all sections. This method can be applied to the security region boundary depiction in the operating scenario of unknown current operating state of power nodes. In a preferred embodiment, for S3, the method of maximizing the sum of the global areas is specifically implemented through the following steps:

[0106] S31: Normalize the unit sensitivity coefficients of all sections, and then add the powers of the q sections after normalization to obtain the added section power , whereby the unit state points of the three projections of all single-section limit constraints are mapped to a new two-dimensional plane - In. This method can directly observe which power node net load distributions have insufficient margins for a certain unit dispatching method, providing a basis for continuing to deduce the supplement measures, and is applicable to the security margin verification during monthly and weekly mode pre-arrangements.

[0107] For the unit three-mapping (projection) section powers of all sections, that is, the transformed unit section powers , denote = , first divide by to complete the normalization of the unit sensitivity coefficients, and then add the powers of the q sections after normalization. Denote the added unit section power as , then the expression is as follows:

[0108] ;

[0109] Among them, represents the normalized sensitivity coefficient of unit node i for section j, denoted as the combined sensitivity coefficient, , , respectively represent the output base value, fluctuation amplitude and fluctuation noise element of unit node i affecting section j.

[0110] According to the above definition, all the state points of the single-section units are mapped to the two-dimensional plane of the multi-section collaborative planning - wherein each unit state point is mapped to .

[0111] S32: In the two-dimensional plane of the multi-section collaborative planning - the unit sensitivity coefficients of all sections after normalization are jointly sorted as the combined unit sensitivity coefficient, that is, the sorting of the multi-section normalized sensitivity coefficients is denoted as .

[0112] S33: According to the piecewise linear function theorem, the upper boundary function and the lower boundary function are defined to obtain the unit operation domain in the two-dimensional plane - That is, the unit operation domain in the two-dimensional plane can be obtained according to the upper and lower boundary function determination method in step S15 - under the two-dimensional plane.

[0113] S34: Select the unit with the largest combined sensitivity coefficient to increase the output first. When the output of this unit reaches the maximum value, all the sensitivity coefficients corresponding to this unit are removed from the joint sorting, and the joint sorting is updated. Specifically: select the unit with the largest combined sensitivity coefficient to increase the output first, denote the serial number of this unit as u. When the output of this unit reaches the maximum value, all the sensitivity coefficients corresponding to this unit are removed from the joint sorting, and the joint sorting is updated from to .

[0114] S35: Repeat S34 until all the sensitivity coefficients corresponding to all units are removed, and a unit dispatching scheme with the largest sum of the global area (also known as: the largest comprehensive safety margin, the safety domain boundary under multi-section constraints) is obtained, which is the best strategy for unit regulation. It can be considered that the above unit dispatching scheme corresponds to the largest area of the unit joint operation domain enclosed by the head-to-tail connection of the line segments in the two-dimensional plane, that is, it contains the most combinations of the balance power and the section power, and the working condition combinations that can be characterized have the most extensive impact on the power grid. Therefore, it is considered that the The upper bound is the optimal strategy for unit regulation, that is, the boundary of the security region under multi-section constraints. This boundary is the global optimal scheduling scheme for the unit if and only if the upper boundaries of the security regions of all sections are completely inside the operating region of the power node, that is, when the unit regulation margin is low, the obtained scheduling scheme is the optimal scheduling scheme. Otherwise, when the unit regulation margin is high, this scheme will cause margin waste. Regarding the unit regulation margin, the following is a simple explanation: As Figure 4 shown, the green shaded area is the margin waste area, and the blue shaded area is the ideal security region. x1, x2, x3, x4, and x5 are the abscissas of the divided intervals. By dividing into four intervals, the position situations of the two operating regions where margin waste will occur and the position situations of the two operating regions where margin waste will not occur are compared and explained. In Region III of the interval [x3, x4], the security region is completely inside the operating region of the power node, and its upper boundary is completely composed of the unit node function. For intervals II and IV, the upper boundaries of the two sections are different, and the unit node function is greater than the power node function. If the maximum area method is used to determine the unit scheduling scheme within these two interval ranges, the unit node function will be used as the upper boundary of the security region. In fact, limited by the upper boundary of the power node operating state, the fluctuation range of the power node is far from the determined upper boundary of the security region. The resulting safety capacity margin can be regarded as a waste of unit scheduling resources. The security region obtained by the above maximum area delimitation method is not ideal and has redundancy, that is, the solved unit scheduling scheme is not the global optimal scheduling scheme. Therefore, when using the maximum area delimitation method, when the unit regulation margin is low, the obtained scheduling scheme is the optimal scheduling scheme. Since the optimization is complex when the abundance is surplus (the shape of the power node function needs to be considered) and the improvement space is limited, the above maximum area delimitation method can still be used as a relatively fast engineering method under this condition, or as an initial feasible solution for further optimization.

[0115] Another combined delimitation method is the maximum delimitation method by giving the power node margin, that is, maximizing the operating margin of the power node. This method can be applied to depict the boundary of the security region in the operating scenario where the current operating state of the power node is known, that is, this method can quickly identify the existing operating risks of the known (predicted) power node and is applicable to the day-ahead security margin check and the intra-day rolling check. In a preferred implementation manner, for S3, the method of maximizing the operating margin of the given power node is realized through the following steps: For the initial power state point in the initial state points, set the section limit and constraint conditions. When there is a solution for the vector in the constraint conditions, set the objective function and solve the objective function to obtain the optimal solution of the vector; then classify all units into two segments according to the optimal solution of the vector. The first category is all the segments with increased output, and the second category is all the segments without increased output. Then, according to the method of obtaining (solving) the security region by the single-section limit constraint, form the sorting methods for the first category and the second category of units respectively. Thus, the boundary of the multi-section limit constraint security region is formed. More specifically:

[0116] For any initial power state point , consider the power state point . Denote the power state point of the k-th section at time t as , the section limit as , and let K be the total number of sections. It should be noted that , different sections are distinguished by the superscript on the right. The lowercase k represents the k-th section, which is the section number, and K is the total number of sections and also the maximum value of k; The section limit is a general term as it does not involve multiple sections. When there are truly multiple sections, many variables need to be distinguished according to the sections. All points should satisfy the following constraint conditions. The following constraint conditions are the expansion of the section limit constraint and are constraints that should be naturally satisfied for each section. The following constraint conditions are preparations for solving the following optimization problem: where

[0117]

[0118] Among them, represents the influence function of the adjustable part of the unit on the power flow of the k-th section except for the baseline output, represents the sensitivity coefficient of the power of unit node i to the power flow of the k-th section, represents the section limit of the k-th section, represents the section limits of K sections, represents the influence part of all power nodes on the power flow of the k-th section, is the solution set vector of the fluctuation noise of the power of unit nodes, that is, the solution set of the scheduling scheme of the adjustable part of the unit.

[0119] i) If the vector has a solution, then set the objective function as:

[0120] ;

[0121] Among them, represents the sensitivity coefficient of the power of unit node i to the power flow of the j-th section, is the fluctuation amplitude of the power of node i, is the fluctuation noise element of the power of unit node i.

[0122] The obtained after solving the optimization objective can be considered as the optimal solution that simultaneously satisfies the power flow boundary after unit output compensation, the sum of the distances of the power flows caused by power node loads and new energy on all sections (i.e., the sum of the power flow margins) is the largest and satisfies the constraint equation. Then, according to the vector The solution classifies all units into two segments after segmentation. The first category is all the segments with increased output in the adjustable part of the units at the current moment , and the second category is all the segments without increased output in the adjustable part of the units at the current moment 1- . Then, according to the solution method of the security region with single-section limit constraints, the unit sorting methods for the first and second categories are formed respectively, that is, the boundaries of the multi-section limit constraint security region obtained by the maximum boundary method of the given power node margin are formed (the part enclosed by the yellow arc and the black arc and the part enclosed by the dark blue arc and the red arc). Given the current unit dispatch The formation process of the security region in the case is as Figure 5 shown. In the figure, the part enclosed by the yellow arc and the black arc and the part enclosed by the dark blue arc and the red arc, that is, the function and enclosed part and and enclosed part, is the multi-section limit constraint security region obtained by the maximum boundary method of the given power node margin at the known current unit state point. The part enclosed by the green arc and the light blue arc is the multi-section limit constraint security region obtained by the maximum area boundary method, that is, the function and enclosed part. Among them, is the sum of all section limits . , is: the multi-section security region envelope obtained by sequentially reducing / increasing the output of each unit according to the sorting of the multi-section normalization sensitivity coefficients of the units with reducible / addable output at the current moment.

[0123] ii) If the vector has no solution, record:

[0124] = ;

[0125] ;

[0126] ;

[0127] ;

[0128] ;

[0129] Among them, is the solution set vector of the fluctuation noise of the unit node power, is the fluctuation noise element of the power of unit node i, A represents the sensitivity coefficient matrix, represents the sensitivity coefficient of the power of unit node j to the power flow of the i-th section, The matrix representing the fluctuation amplitude of power is the fluctuation amplitude of the power of node i represents the vector of section limit adjustment capabilities required for each section of the unit under the influence of the current power state point represents the section limit of the k-th section represents the base value of the output of unit node i represents the influence part of all power nodes on the power flow of the k-th section represents the product of the sensitivity coefficient matrix and the diagonal matrix of fluctuation amplitudes, which is an intermediate variable

[0130] In case ii), the original constraint condition has no solution, which means that the current power operation state point is outside the safety domain corresponding to the current unit state. There is a situation where no matter how much the output is increased, the power operation state point cannot be within the safety range. Therefore, by finding the minimum norm method, the shortest distance from the current power operation state point outside the domain to the safety domain can be found. Then, through this distance, the point on the safety domain closest to the power operation state point outside the domain is inversely calculated. This point is the best scheduling plan that the current unit can adopt to enclose the power operation state point

[0131] Therefore, taking the minimum norm with respect to the distance from y as the objective function

[0132] ;

[0133] where , is the new matrix formed by inserting a row of all 1s at the end of A (the optimization problem expressed in matrix form originally lacks the constraint condition of power balance. Therefore, the power balance constraint is added in the form of interpolation), is after adding as the last element to form a new matrix. For the matrix generated by the above method, if the sensitivity of the section constraint is linearly related to the added row, then the row corresponding to this section is removed in the matrix . If the sensitivities of the two section constraints are linearly related, they are combined and considered as the same section. After the above processing, should be row full rank, and the optimization problem can obtain a unique solution, and its solution expression is

[0134] ;

[0135] Through the above method, the initial value of the unit solution closest to the net load distribution of the power nodes can be obtained. Then, by using the method in the aforementioned i), after forming the boundary of the security region, make up for all the overstepping parts, and a new security region that envelopes the fluctuation range of the power nodes can be formed. The new security region here is a means to forcibly expand the scope of the security region by taking further make-up measures to enclose the power state point when the original power state point is not within the security region, that is, when the original constraint conditions have no solution. This belongs to the subsequent security region make-up measures and is not covered by the technical problems solved by the present invention. Therefore, the specific means are not discussed in the present invention.

[0136] S4: Establish a stochastic fluctuation model for the operating state of power nodes. According to the shortest distance and direction between the fluctuation boundary of this model (when the model performs an affine transformation outward from the geometric center, a polygonal fluctuation domain is formed, and the boundary of this polygonal fluctuation domain is the fluctuation boundary of the model) and the boundary of the multi-section quota constraint security region corresponding to each section, give an effective reserve formula, and measure the reserve capacity of the power system through the effective reserve formula. Calculate an effective reserve for each single-section security region, and then take the minimum value of all reserves. It is specifically implemented through the following steps:

[0137] In the scenario considering the stochastic fluctuation of the net load of power nodes, for each power operating state point in the power node operating domain at each moment , there will be a stochastic fluctuation range.

[0138] S41: Assume that each power node changes with a volatility of centered around the power state point , where . Denote as the fluctuation amplitude of the power of node i, and the change range is . Then, when all power node fluctuations are reflected in the operating domain, the fluctuation interval is: a polygonal envelope formed by the power node operating domain with the power state point as the center and the side length reduced to 2 of the original length. This is the polygonal envelope of the fluctuation interval, that is, Figure 6The polygonal fluctuation domain geometrically similar to the power node operation domain shown in []. Denote the probability of the power operation state point having a volatility of λ as Φ. For a given probability Φ, the volatility λ corresponding to different time scales is different, that is, the distributions of the power node fluctuation variables at different time scales are different. The smaller the prediction time scale, the smaller the volatility λ. Therefore, the fluctuation interval range of monthly prediction will be much larger than that of day-ahead prediction (considering temperature-sensitive loads), and the day-ahead prediction will be larger than the two-hour-ahead intra-day prediction (only considering the fluctuation of new energy output). The fluctuation interval shrinks to a state point in the real-time state. It should be noted that d is the long-term fluctuation amplitude of the node originally based on long-term statistics, but when observing only short-term fluctuations, its fluctuation amplitude is often shorter than the long-term statistical quantity. Therefore, λ represents the ratio relationship of the short-term fluctuation amplitude to the long-term statistical amplitude. Since the difference between the long-term and short-term fluctuation scenarios lies only in that the fluctuation amplitude becomes 2λ times the original, and the formation process of the power node operation domain is the same, the side length of the short-term node operation domain relative to the original envelope only becomes 2λ times the original. According to the above characterization of the power node fluctuation in the two-dimensional plane of the operation domain, it can be considered that the power node fluctuation interval can be characterized by a piecewise linear boundary function polygon envelope. When the volatility λ gradually increases, the polygon envelope of the fluctuation interval expands proportionally with the power state point as the center, that is, an affine transformation with as the center, as shown in Figure 6 .

[0139] S42: Assume that the center of the power state point function (power state point) is located inside the safety domain corresponding to the observed cross-section. Connect the center of the power state point function with each vertex of the polygon envelope of the power node fluctuation interval and extend it. The extended line intersects the safety domain boundary to obtain the intersection point of the extended line and the safety domain boundary. The length of the line connecting the intersection point to the center of the power state point function is d1. When the ratio of d1 to the length d0 of the line connecting the corresponding vertex to the center of the power state point function is the smallest, this d1 is the shortest fluctuation distance from the power node function center to the unit node function. The product of the shortest fluctuation distance and the reserve coefficient is defined as the effective reserve of the observed cross-section. The solution process of the effective reserve by the analytical geometry method under a single cross-section is shown in Figure 7 , as shown in Figure 7 , where Indicates the effective reserve of the observed section (section effective reserve), which is shown as a line segment in the figure; i represents the power node number, that is, power node i, which can be understood as any power node. Power node i is the intersection point of the extension line and the fluctuation boundary (i.e., the envelope polygon of the power node fluctuation range in the figure), which is shown as a point in the figure; j' represents the clockwise numbering of the unit nodes determined by the maximum bounding method according to the given power node margin corresponding to the net load growth direction of the power nodes in the k-th section, and is the unit node number corresponding to the intersection point of the extension line and the safety domain boundary, which is shown as a point on the figure. When considering all sections of the system, the minimum value of the section effective reserve is taken and defined as the system effective reserve R:

[0140] ;

[0141] According to the above solution process of the section effective reserve By using the analytical geometry method to obtain , The expression can be shown as follows:

[0142] ;

[0143] ;

[0144] ;

[0145] ;

[0146] ;

[0147] ;

[0148] ;

[0149] ;

[0150] Among them, is the horizontal angle between the center point of the operating region boundary function of the power nodes in the k-th section and the corresponding point of the i-th power node, is the unit reserve coefficient, is the fluctuation amplitude of the i power node, is the maximum peak shaving capacity of the unit at the i node, is the value of the fluctuation noise element at node i at time t, G is the admittance coefficient of the k-th section, is the sensitivity coefficient of the power node i to the k-th section, is the sensitivity coefficient of the unit at the i node to the k-th section, Indicates The sensitivity coefficient of the unit at the node to the k-th section is the upper bound of the net load of the power node, is the lower bound of the unit output, is the difference between the active power corresponding to the th node of the unit node operation domain boundary function of the kth section and the active power corresponding to the center point of the power node operation domain boundary function, is the difference between the section active power corresponding to the th node of the unit node operation domain boundary function of the kth section and the section active power corresponding to the center point of the power node operation domain boundary function. m is the total number of power nodes, n is the total number of unit nodes, K is the total number of sections, and j' is the clockwise numbering of the unit nodes under the unit dispatch plan determined by the maximum bounding method according to the given power node margin corresponding to the net load growth direction of the power node in the kth section.

[0151] It should be noted that the power node operation state discussed in the present invention is carried out under the assumption that the net load of each power node has not reached the extreme value in advance. This can be used as a simple model in monthly checking, but the influence when the net load of the power node fluctuates and touches the limit needs to be considered in day-ahead or intra-day checking, because the net load of the power node that reaches the extreme value will not continue to fluctuate according to the ideal fluctuation interval, thus changing the shape of the random fluctuation interval. In this case, the effective reserve direction to be obtained should be corrected in order to obtain the correct .

[0152] In summary, based on the above embodiments, compared with the prior art, the present invention can achieve the following beneficial effects:

[0153] 1. The present invention models the new energy output, load fluctuation and unit adjustable range through interval variables, forming an affine linear equation solution set covering all possible operation states. This method can comprehensively capture the randomness, volatility of new energy and load uncertainty, avoid the checking omission problems caused by traditional methods ignoring extreme working conditions or combined scenarios, and significantly improve the system robustness. At the same time, by obtaining the operation domain (unit and power node operation domain), the distribution states of new energy fluctuation and load fluctuation and the change of unit output state can be incorporated into a unified operation state domain, and the influence of unit output combination and random fluctuations such as new energy and load on the section power flow can be quantified. By mapping the operation boundary accommodating all unit operation states to the two-dimensional plane of section power - balanced power, it can provide theoretical support for the safety monitoring of unit and power node operation states.

[0154] 2. The present invention linearly maps a high-dimensional state space to a two-dimensional plane reflecting section power and balanced power, and constructs a safety region satisfying multiple constraints through geometric operations such as flipping and translation. It transforms a complex high-dimensional optimization problem into an intuitive two-dimensional geometric analysis, greatly reducing the computational complexity. At the same time, through the visual boundary of the safety region, it is convenient for dispatchers to monitor the system safety margin in real time. Meanwhile, the proposal of the safety region enables the effective quantification and visualization of the safety margins under single-section and multi-section conditions considering unit regulation, new energy, and load fluctuations. By giving two methods for adjusting the unit to maximize the safety margin, it improves the regulation efficiency of the unit for section power flow. The interval power flow method provides full-condition coverage, and the two-dimensional projection simplifies the computational complexity. The combination of the two achieves efficient analysis while ensuring accuracy.

[0155] 3. The present invention proposes two principles for characterizing the safety region boundary. One is the maximum area delimitation method: through the joint sorting of normalized sensitivity coefficients, it preferentially adjusts the units with the greatest impact on multiple sections to ensure the maximum sum of the safety margins of the entire region, which is applicable to medium- and long-term planning. The other is the maximum given power node margin delimitation method: it approximates the net load distribution of power nodes with minimum norm optimization, quickly identifies and compensates the risk points of key sections, and is applicable to short-term rolling checks. The two methods are respectively applied to the operation scenarios of unknown and known current power node operating states, taking into account global optimization and local risk prevention and control, and improving the regulation efficiency and safety under multi-section constraints. Moreover, the maximum area method is applicable to long-term planning, and the given margin method is suitable for short-term checks. The two methods cooperate to meet the standby requirements of different time scales.

[0156] 4. The introduction and solution of the effective standby concept can not only be used to obtain the standby direction with the greatest possible overstep under the net load fluctuation of power nodes, so that the added standby can improve the overstep situation of the observed section to the greatest extent, but also make the risk perception of grid section overlimits more refined. By introducing the standby with section limit constraints, it can avoid the chain reaction caused by section overlimit accidents due to the overly optimistic traditional standby calculation method and avoid the dispatching losses caused by standby hard gaps.

[0157] In summary, the present invention can cover the full-dimensional uncertainties of new energy fluctuations, load changes, and unit regulation, solve the problem of massive working condition checks. And through two-dimensional projection and geometric operations, it transforms complex optimization problems into intuitive calculations, significantly improving the efficiency of standby capacity measurement. In addition, multi-section collaborative optimization and effective standby directional configuration ensure the safe and stable operation of the system in high-proportion new energy scenarios. Moreover, through the effective standby calculation of the present invention, the standby requirements can be accurately quantified, redundant configuration can be reduced, and the grid operation cost can be lowered.

[0158] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above method embodiments. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), or the like.

[0159] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification. Moreover, the above embodiments only represent several implementation manners of the present invention. The description is relatively specific and detailed, but it cannot be understood as a limitation to the scope of the present invention. For those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention.

Claims

1. A method for calculating the reserve capacity of a power system based on multi-constraint security domain projection, characterized in that Including: S1: Extract the power flow fluctuation characteristic quantities of the power grid by the interval power flow method to construct a state space representing the operation state of the power grid, linearly transform the state space to a two-dimensional projection plane reflecting the relationship between section power and system power, and then obtain the operation domain satisfying the constraint conditions by determining the upper and lower boundary functions; the initial state points of the unit nodes and power nodes at any moment in space are the state space; the nodes with new energy and / or load are power nodes; the initial state points are represented by affine linear equations. S2: Introduce section limit constraints on the basis of the operation domain to obtain the single-section limit constraint safety domain. S3: Combine the acquisition method of the single-section limit constraint safety domain and, with the principle of maximizing the sum of the global areas and maximizing the operation margin of the given power nodes, depict the boundaries of two multi-section limit constraint safety domains respectively for the operation scenarios of unknown current operation states of power nodes and known current operation states of power nodes. S4: Establish a stochastic fluctuation model for the operation states of power nodes, give the effective reserve formula according to the shortest distance and direction between the fluctuation boundary of the model and the boundaries of the multi-section limit constraint safety domains corresponding to each section under any of the operation scenarios, and calculate the reserve capacity of the power system through the effective reserve formula. S4 Including: S41: Assume that each power node varies with a power state point as the center at a volatility, and the variation range is . Then, the fluctuations of all power nodes are reflected in the operation domain. With the power state point as the center, the polygon envelope formed by the operation domain of power nodes with the side length reduced to 2λ of the original length is the polygon envelope of the fluctuation interval; When the volatility λ gradually increases, the fluctuation interval polygon envelope increases proportionally with the power state point as the center; d is the fluctuation amplitude of the power of node i. S42: Assume that the center of the power state point function is located inside the safety domain corresponding to the observed section, connect the center of the power state point function with the vertices of the power node fluctuation interval envelope polygon and extend them, the extended lines intersect with the safety domain boundary to obtain the intersection points of the extended lines and the safety domain boundary, and when the ratio of the connection length d1 from the intersection point to the center of the power state point function to the connection length d0 from the corresponding vertex to the center of the power state point function is the smallest, this d1 is the shortest fluctuation distance from the center of the power node function to the center of the unit node function. S43: Define the product of the shortest fluctuation distance and the direction as the effective reserve of the section , ； is the horizontal included angle between the center point of the operating region boundary function of the k-th section power node and the corresponding point of the i-th power node, is the unit reserve coefficient, is the difference between the active power corresponding to the node of the unit node operating region boundary function of the k-th section and the active power corresponding to the center point of the power node operating region boundary function; When considering all sections of the system, take the minimum value of the effective reserve among them and define it as the system effective reserve R.

2. The method for measuring the reserve capacity of a power system based on multi-constraint security domain projection according to claim 1, wherein S1 includes: S11: Introduce interval variables to model the fluctuation ranges of new energy and load and the adjustable range of the unit to form a power flow equation containing interval variables, and define the nodes with new energy and / or load as power nodes. S12: Obtain the initial state points of the unit nodes and power nodes at any moment in space as the state space, and calculate the branch power flows between each node. S13: Construct a two-dimensional projection plane 1 with section power as the y-axis and system power as the x-axis according to the branch power flow, system total power and power flow equation, and set section limit constraints and balanced power constraints, and split and map the initial state points on the two-dimensional projection plane 1 to obtain the unit and power state points of the first projection. S14: Combine the transformation of the system power with the deformation of the power balance constraint, and split and map the initial state points on the two-dimensional projection plane 2 with section power as the y-axis and the transformed system power as the x-axis to obtain the unit and power state points of the second projection. S15: Define the upper and lower boundary functions of the unit and power state points for the secondary projection respectively, and obtain two piecewise linear and closed polygon envelopes. The enclosed regions are the operation domains of the unit and the power node respectively.

3. The method for measuring the reserve capacity of a power system based on multi-constraint security domain projection according to claim 2, wherein In S11, the modeling adopts the affine-linear optimization method, incorporates the adjustable range of the unit and the fluctuation ranges of new energy and load nodes into the node injection power respectively, and establishes an affine-linear equation representing the fluctuation.

4. The method for measuring the reserve capacity of a power system based on multi-constraint security domain projection according to claim 2, wherein S2 includes: Transform the section power in combination with the deformation of the section limit constraint. First, perform a symmetric flip of the unit node operation domain obtained in S15 about the x-axis and then translate it upward. The translation distance is the section limit size to obtain the transformed unit operation state. Complete the multiple splitting and mapping of the initial state point on the two-dimensional projection plane three with the transformed section power as the y-axis and the transformed system power as the x-axis to obtain the unit and power state points of the three-time projection with single-section constraint. Define the intersection of the region below the upper boundary function of the transformed unit operation state and the entire domain of the power node operation domain as the single-section limit constraint safety domain.

5. The method for measuring the reserve capacity of a power system based on multi-constraint security domain projection according to claim 2, wherein In S2, give the unit scheduling plan that maximizes the area of the single-section limit constraint safety domain.

6. The method for calculating the reserve capacity of a power system based on multi-constraint security domain projection according to claim 5, wherein In S2, the unit scheduling plan that maximizes the area of the single-section limit constraint safety domain adopts: the units increase their output in sequence on the upper boundary of the single-section limit constraint safety domain.

7. The method for calculating the reserve capacity of a power system based on multi-constraint security domain projection according to claim 4, wherein In S3, the method for maximizing the sum of the areas of all domains is the method of obtaining the boundary of the safety domain with the largest area after incorporating all sections into the same coordinate system.

8. The method for measuring the reserve capacity of a power system based on multi-constraint security domain projection according to claim 2, wherein In S3, the method for maximizing the given power node operation margin includes: for the initial power state point in the initial state point, set the section limit and constraint conditions. When there is a solution for the vector in the constraint conditions, set the objective function and solve the objective function to obtain the optimal vector solution; then classify all units into two segments according to the optimal vector solution and categorize them. The first category is all the segments with increased output, and the second category is all the segments without increased output. Then, according to the method for obtaining the single-section limit constraint safety domain, form the unit sorting methods for the first category and the second category respectively. Thus, the boundary of the multi-section limit constraint safety domain is formed.

9. The method for calculating the reserve capacity of a power system based on multi-constraint security domain projection according to claim 1, wherein According to S42 and S43, the effective reserve is obtained by the analytic geometry method .

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